Home/Algebra/Matrix decompositions/Low-rank approximation23. Matrix decompositionsLow-rank approximationLevel: avanzadoIn 23. Matrix decompositionsFormulaCopy LaTeXAk=∑i=1kσiuiviTA_k=\sum_{i=1}^{k}\sigma_i u_i v_i^TAk=i=1∑kσiuiviTTagsalgebradecompositionsdecompositions matricesalgebra formulalinearDetailApproximates a matrix using its k dominant singular values.Explore the ideaFound an error? Contact us.Related formulasRelatedSVDA=UΣVTA=U\Sigma V^TA=UΣVTOpen formulaOpen in sectionRelatedRankrank(A)=dim(Col(A))\operatorname{rank}(A)=\dim(\operatorname{Col}(A))rank(A)=dim(Col(A))Open formulaOpen in section